Triple
T10194637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pet |
E238129
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Kiki Miyake
Kiki Miyake is a producer known for her work in the entertainment industry, particularly in projects involving pets or animal-related content.
|
E848158
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kiki Miyake | Statement: [Pet, producer, Kiki Miyake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiki Miyake Context triple: [Pet, producer, Kiki Miyake]
-
A.
Kayo Washio
Kayo Washio is a Japanese television and film producer best known for her executive production work on the crime drama series "Tokyo Vice."
-
B.
Kazumi Ōta
Kazumi Ōta is a Japanese politician who serves as the mayor of Kashiwa in Chiba Prefecture.
-
C.
Masami Nakagawa
Masami Nakagawa is a Japanese physicist known as a prominent student and collaborator of theoretical physicist Shoichi Sakata.
-
D.
Teru Ando
Teru Ando was a Japanese sculptor best known for creating the iconic bronze statue of the loyal dog Hachiko in Tokyo.
-
E.
Yoko Suzuki
Yoko Suzuki was the wife of former Japanese Prime Minister Zenko Suzuki and served as Japan’s First Lady during his tenure in office.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kiki Miyake Triple: [Pet, producer, Kiki Miyake]
Generated description
Kiki Miyake is a producer known for her work in the entertainment industry, particularly in projects involving pets or animal-related content.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kiki Miyake Target entity description: Kiki Miyake is a producer known for her work in the entertainment industry, particularly in projects involving pets or animal-related content.
-
A.
Kayo Washio
Kayo Washio is a Japanese television and film producer best known for her executive production work on the crime drama series "Tokyo Vice."
-
B.
Kazumi Ōta
Kazumi Ōta is a Japanese politician who serves as the mayor of Kashiwa in Chiba Prefecture.
-
C.
Masami Nakagawa
Masami Nakagawa is a Japanese physicist known as a prominent student and collaborator of theoretical physicist Shoichi Sakata.
-
D.
Teru Ando
Teru Ando was a Japanese sculptor best known for creating the iconic bronze statue of the loyal dog Hachiko in Tokyo.
-
E.
Yoko Suzuki
Yoko Suzuki was the wife of former Japanese Prime Minister Zenko Suzuki and served as Japan’s First Lady during his tenure in office.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdedc7cc748190bceb8f657afcc054 |
completed | April 2, 2026, 4:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d32aef701c8190a01e632eb4fda1b9 |
completed | April 6, 2026, 3:39 a.m. |
| NEDg | Description generation | batch_69d32b784dd48190be1e9ab9c36c224e |
completed | April 6, 2026, 3:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d3481d882c8190be8653289b712d08 |
completed | April 6, 2026, 5:43 a.m. |
Created at: March 30, 2026, 9:13 p.m.